Where our data comes from:

Our data comes from the National Institute on Drug Abuse's (NIDA) Drug Overdose Death Rates dataset. The original dataset compiles information on drug overdoses from opioids (further dissected into prescription opioids, synthetic opioids, and Heroin) and stimulants (split into cocaine and psychostimulants/methamphetamines). These data were also organized by gender, race, and drug type, and presented as deaths per 100,000 individuals. Read more about our dataset on our "Critique" page. 

How our data was processed:

Thanks to the completeness of the original dataset, in the "cleaning" stage of our project we did not need to alter or remove any individual values. However, for the purposes of simplifying our visualization process, we duplicated our dataset and edited the duplicates to contain just the specific variables we wants to visualize in each graph. View our cleaned dataset on our "Critique" page.

We used Tableau, a popular visual analytics platform, to visualize our data in different ways. We were curious about what identity factors, such as age and race, impacted rates of opioid overdose, as well as how these data changed over time. Thus, our visualizations aimed to show chronological change in overdose rates, plotted against various identity factors. We were also curious about which types of opioids were most implicated in growing overdose rates, so we also visualized the data based on opioid type. View our data visualizations on our "Visualizations" page.

How our data is presented:

We are using Google Sites to host this project, as it is reliable and good for simultaneous group collaboration. In our web design, we have considered accessibility practices by choosing simple design, fonts, and images. We have also endeavored to closely follow the most recent publishing of the Web Content Accessibility Guidelines (WCAG 2.0).

Our data visualizations have been embedded into the website from Tableau. We have chosen this option in order to retain minor, but important, interactive elements from Tableau, such as the ability to provide labels that appear when users scroll over the visualized data. View our data visualizations on our "Visualizations" page.

• 6/7/24: We chose to focus our project on opioid overdoses because we were interested in approaching this issue from a social justice perspective, informed by Critical Race Theory and an intersectional perspective in order to better contextualize the current opioid epidemic in current social issues.

• 6/10/24: We decided to use the National Institute on Drug Abuse's (NIDA) most recent dataset (1999-2022), instead of our original dataset (1999-2019). This is because our preliminary research has informed us that opioid overdoses increased dramatically with the start of the COVID-19 epidemic. We believe it is necessary to include the most recent data available in order to be able to accurately comment on how these issues are impacting society in our current moment. 

• 6/12/24: Our group decided to design the landing page of the website in a way that gives context to the project first, rather than letting the data and visualizations speak for themselves. We believe given the serious implications of drug overdose data and the potential for these data to be used to negatively stereotype certain communities, or increase police surveillance in specific communities, it is crucial to provide context to the project.

• 6/18/24: Although we initially wanted to utilize interactive visualizations in our project, due to time limitations and our unfamiliarity with Tableau, we decided to use static visualizations instead. 

• 6/24/24: We decided to diversify the visualizations used in our project in order to show the data from many different angles.

• 6/10/24: Sia, Tati, and Steph met to discuss dataset options

• 6/11/24: The entire group met to discuss and finalize dataset

• 6/12/24: Steph, Sia, Ruya, Chris met to discuss and work on Storyboard

• 6/17/24: Ruya and Jacob met with Manish to discuss the progress of the project

• 6/17/24: Ruya worked on the Storyboard

• 6/18/24: Ruya submitted the Storyboard

• 6/18/24: Chris created the website on Google Sites so the group could collaboratively work on it

• 6/19/24: Steph and Tati met to discuss the Data Narrative; Tati drafted the Data Narrative

• 6/20/24: All group members worked on the "About" page and bios

• 6/20/24: Jacob and Steph met to work on creating visualizations on Tableau; Jacob created the visualizations on Tableau

• 6/20/24: Steph compiled and annotated the bibliography

• 6/20/24: Tati and Steph completed the Data Narrative draft

• 6/20/24: Chris updated the website to conform with the Web Content Accessibility Guidelines (WCAG 2.0)

• 6/20/24: Tati submitted the "About" and "Narrative" pages

• 6/22/24: Steph submitted the "Bibliography" page

• 6/23/24: Sia and Steph worked on the Data Critique

• 6/24/24: Sia, Jacob, and Steph met with Manish to discuss the progress of the project

• 6/24/24: Jacob worked on creating new data visualizations

• 6/24/24: Steph reorganized the website, added images/alt text, and worked on the "Home page"

• 6/24/24: Sia and Steph worked on the Data Critique

• 6/25/24: Chris proof-read and adjusted/added alt-text as needed for final accessibility guidelines check

• 6/25/24: Tati created a timeline for the Data Narrative

Thank you to the 2024 UC Berkeley Digital Humanities 100 instructional team—Andressa Maia, Eliza Breder, Rebecca Baugh, and Manish Kumar—for their guidance and for the engaging conversations they facilitated throughout the course.